摘要
针对汽车电动助力转向与主动悬架集成系统控制的复杂性、不确定性及非线性,应用灰色预测理论、模糊控制理论和神经网络控制理论,提出电动助力转向与主动悬架集成系统动态性能灰预测模糊神经网络控制策略,研究集成系统的动态响应,设计以单片机LPC2138为内核的集成系统控制器。在仿真的基础上,进行实车道路试验。结果表明,采用灰预测模糊神经网络控制可对汽车电动助力转向与主动悬架的集成系统进行实时协调控制,汽车行驶平顺性改善的同时,缓解汽车转向时安全性与操纵稳定性之间的矛盾,提高整车综合性能。
Aiming at complexity, uncertainty and non-linearity of electric power steering and active suspension integrated system, the grey prediction fuzzy neural network control strategy of dynamic performance of integrated system is proposed based on the grey prediction theory, fuzzy control theory and neural network control theory. The dynamic response of integrated system is studied. The integrated system controller with chip microprocessor LPC2138 as kernel is designed. Based on the simulation, the real vehicle road test is done. The results show that the grey prediction fuzzy neural network control strategy can carry out real time coordinated control of the integrated system of electric power steering and active suspension, the contradiction between the ride comfort and the handling stability is alleviated and the comprehensive performance is improved.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2009年第6期128-133,共6页
Journal of Mechanical Engineering
基金
国家自然科学基金(50875112)
江苏省教育厅自然科学基金(08KJB580001)
江苏大学高级人才启动基金(07JDG039)资助项目
关键词
电动助力转向
主动悬架
集成系统
智能控制
Electric power steering Active suspension Integrated system Intelligent control
